Music recommendation systems and services such as Pandora, Ringo and Spotify are popular ways for users to find and listen to music that may be of interest to them. However, such music recommendation services or applications (software) identify music for the user to listen to based on the user's personal preferences as indicated by the user. For example, the user can indicate his preferences through manual selection or some other type of affirmative user action indicating the user's preferences, e.g., by clicking on a “like” icon or providing a rating. The recommendation may also be made based on previous user selection history or similar other users selections. However, such music recommendation systems and services are relatively inflexible in that they generally do not take into account changing music preferences of users at different times, such as according to users moods and wellness. Taking such factors into consideration can enhance recommendation choices and user experience.